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Bayesian Inference for Rayleigh Distribution Under Step-Stress Partially Accelerated Test with Progressive Type-II Censoring with Binomial Removal

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Abstract

In this paper, we propose maximum likelihood estimators (MLEs) and Bayes estimators of parameters of the step-stress partially accelerated life testing of Rayleigh distribution in presence of progressive type-II censoring with binomial removal scheme under Square error loss function, General entropy loss function and Linear exponential loss function . The MLEs and corresponding Bayes estimators are compared in terms of their risks based on simulated samples from Rayleigh distribution. Also, we present to analyze two sets of real data to show its applicability.

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Acknowledgements

The authors wish to thank editor-in-chief, associate editors and the referee for their valuable comments without which the paper could not have taken its present form.

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Authors and Affiliations

  1. Department of Statistics, Central University of Haryana, Mahendergarh, Haryana, India

    Manoj Kumar & Anurag Pathak

  2. Department of Statistics, Central University of Rajasthan, Kishangarh, Rajasthan, India

    Sukriti Soni

Authors
  1. Manoj Kumar
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  2. Anurag Pathak
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  3. Sukriti Soni
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Correspondence to Manoj Kumar.

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Kumar, M., Pathak, A. & Soni, S. Bayesian Inference for Rayleigh Distribution Under Step-Stress Partially Accelerated Test with Progressive Type-II Censoring with Binomial Removal. Ann. Data. Sci. 6, 117–152 (2019). https://doi.org/10.1007/s40745-019-00192-w

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